国外近十年深度学习实证研究综述——主题、情境、方法及结果

A Literature Review of 10-year Empirical Studies of Deep Learning Abroad:Themes, Context, Methods and Outcomes

为厘清国外教育领域深度学习的研究进展,选取Web of Science、Springer、ScienceDirect等数据库的85篇文献(2008—2018年),依据实证研究的核心要素建立编码体系进行内容分析。结果表明:(1)研究主题集中在深度学习策略、方式和评价三个方面;(2)比格斯、马顿&塞尔乔、恩特威斯尔&拉姆斯顿提出的深度学习概念框架得到较多认可;(3)深度学习在各类学科情境中广泛应用,但研究对象多为大学生;(4)实证研究数据呈现以量化分析为主、质性分析为辅的特征,混合分析日益得到重视;(5)自我报告量表、编码标准、条件化测量、眼动追踪是深度学习的主要测量方法;(6)深度学习的有效性突出表现在学业成绩、知识理解、学习体验、思维与能力发展等方面。

In order to clarify the research progress of deep learning in education abroad , 85 papers are selected from Web of Science, Springer, ScienceDirect and other databases (2008-2018). Then a coding system is established based on the core elements of empirical research for content analysis.The results indicate that:(1) the research themes mainly focus on three aspects of deep learning strategies, approaches and evaluation;(2) The conceptual frameworks of deep learning proposed by Biggs, Marton & Saljo and Entwistle are widely recognized;(3) Deep learning is closely used in various subject contexts, but the research objects are mostly college students;(4) Research data is mainly analyzed by quantitative methods , which is supplemented by qualitative methods, while mixed analysis is increasingly valued;(5) Self-report scale, coding standard, conditional measurement and eye movement tracking are the main measuring methods of deep learning;(6) The effectiveness of deep learning is highlighted in academic performance, knowledge understanding, learning experience, the development of thinking and competence.